Latent semantic analysis-based image auto annotation

Abstract

The image retrieval is a particular case of information retrieval. It adds more complex mechanisms to relevance image retrieval: visual content analysis and/or additional textual content. The image auto annotation is a technique that associates text to image, and permits to retrieve image documents as textual documents, thus as in information retrieval. The image auto annotation is then an effective technology for improving the image retrieval. In this work, we propose the AnnotB-LSA algorithm in its first version for the image auto-annotation. The integration of the LSA model permits to extract the latent semantic relations in the textual describers and to minimize the ambiguousness (polysemy, synonymy) between the annotations of images.